Dyslipidemias play a large role in the occurrence of cardiovascular disease, which has fueled interest to better understand environmental factors responsible for dyslipidemias, especially hypertriglyceridemia. Epigenetic variations may affect triglyceride (TG) metabolism and response to environmental challenges. Our goal is to conduct the first experiments that will comprehensively scan the epigenome for determinants of TG and other dyslipidemic responses to two environmental interventions, one to raise TGs (a high-fat meal), and one to lower TGs (3-week fenofibrate treatment). These experiments will be conducted in the NHLBI Program in Gene-Environment Interaction Network's Genetics of Lipid Lowering and Diet (GOLDN) study. GOLDN recruited family members from field centers in Minnesota and Utah and phenotyped them extensively for enzymatic and NMR lipids and inflammatory markers in response to the two interventions. The proposed study will build upon this unique resource using previously collected samples to implement the following aims: (1) Conduct genome-wide CpG methylation analysis, using next generation sequencing method, specifically, Reduced Representation Bisulfite Sequencing, in 1,048 individuals from 184 families to identify epigenetic variation contributing to the response of TGs and TG-related phenotypes to a fat meal, fenofibrate, and a fat meal in the context of fenofibrate treatment. From these results, we will select 20 candidate genes with the best evidence for further characterization in Aim 2. (2) Characterize the methylation state of these 20 genes using bisulfite sequencing of promoters and other regions of interest in all 1,048 family members. (3) Replicate significant findings from Aims 1 and 2 in external cohorts. (4) Conduct gene expression studies to identify the functional impact of methylation findings from Aims 1-3 since DNA methylation may affect the expression of nearby genes in a variety of ways, including transcription rates, alternative splicing, microRNA inhibition, or allele specific expression. We will apply next-generation sequencing to both mRNA and microRNA from 150 subjects using a method called RNAseq. If successful, we will identify novel epigenetic variations that predict individuals who respond poorly to dietary fat or favorably to fenofibrate which will lead to the development of targeted interventions to more effectively prevent and treat hypertriglyceridemia.